Discover 4 peer-reviewed studies in Ai Assisted Decision Making (2024–2025). Explore research findings powered by Prolific's diverse participant panel.
This page lists 4 peer-reviewed papers in the research area of Ai Assisted Decision Making in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.
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Authors: JY Bo, S Wan, A Anderson
Year: 2025
Published in: Proceedings of the 2025 CHI Conference ..., 2025 - dl.acm.org
Institution: University of Toronto
Research Area: Appropriate reliance on LLM, Human-Computer Interaction, AI-assisted decision making.
Discipline: Human-Computer Interaction
This paper explores the latest advancements and key trends in the field of Human-Computer Interaction (HCI), focusing on novel interfaces and user experience paradigms.
Citations: 25
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Authors: P Spitzer, K Morrison, V Turri, M Feng, A Perer
Year: 2025
Published in: ACM Transactions on ..., 2025 - dl.acm.org
Institution: Carnegie Mellon University, Karlsruhe Institute of Technology, University of Bayreuth
Research Area: Explainable AI (XAI), AI-Assisted Decision-Making, Human-AI Collaboration
Discipline: Artificial Intelligence
The study highlights how imperfect explainable AI (XAI), along with human cognitive styles, affects reliance on AI and the performance of human–AI teams, providing design guidelines for better collaboration systems.
Methods: The researchers conducted a study with 136 participants, analyzing the effects of explanation imperfections and cognitive styles on AI-assisted decision-making and human–AI collaboration.
Key Findings: The impact of incorrect explanations and explanation modalities on human reliance, decision-making, and human–AI team performance, as well as the role of cognitive styles.
Citations: 2
Sample Size: 136
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Authors: V Robbemond, O Inel, U Gadiraju
Year: 2024
Published in: ... of the 30th ACM Conference on ..., 2022 - dl.acm.org
Institution: V Robbemond: Delft University of Technology, O Inel: Delft University of Technology, U Gadiraju: Delft University of Technology
Research Area: Explanation Modality in AI-assisted Decision Making
Discipline: Human-Computer Interaction
The study explores the role of explanation modalities in AI-assisted credibility assessment tasks, finding that combined modalities (text and/or audio with graphics) enhance accuracy, trust, and usability compared to single-modality approaches.
Methods: A between-subjects experiment was conducted with six explanation modalities to evaluate their influence on user performance, trust, and usability in credibility assessments.
Key Findings: The effects of different explanation modalities on decision accuracy, system trust, and usability in an AI-assisted credibility assessment system.
DOI: 10.1145/3503252.3531311
Citations: 47
Sample Size: 375
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Authors: A Bashkirova, D Krpan
Year: 2024
Published in: Science Direct
Institution: London School of Economics and Political Science
Research Area: AI-assisted Decision Making, Confirmation Bias, Professional Trust, Psychology, AI Bias
Discipline: Behavioral Science, Psychology
